Paper Title
Edge Based Classifier For Secret Hiding Using Lsb Steganography on Images With Improved Ceaser Cipher Cryptography

Abstract
In recent years, Steganography is the field of user authentication and data privacy. This paper introduced a novel, principled concept to detect LSB steganography in digital video. It is exposed that the hidden message’s length is embedded within least significant bits of image data and it could be accessed through comparatively maximum accuracy. This novel steganalysis approach is based some edge based classifier like Fuzzy Random Forest (FRF) classifier. Here the edge detection is carried out with the improved canny edge detector. Edge detected and non-edge detected pixels are used for the embedding process and in which X and Y secret bits from the Modified Caesar cipher is hidden in the corresponding edge and non-edge pixels. The resulting methodology is simple and fast. To examine the robustness of the proposed methodology, result is compared with the two recent techniques. The result shows our prosed work is secured in case of high embedding efficiency. Index Terms - Steganography, cryptography, edge detection, classification, security, embedding efficiency.